Exploring Topical Lead-Lag across Corpora

IEEE Trans. Knowl. Data Eng.(2015)

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摘要
Identifying which text corpus leads in the context of a topic presents a great challenge of considerable interest to researchers. Recent research into lead-lag analysis has mainly focused on estimating the overall leads and lags between two corpora. However, real-world applications have a dire need to understand lead-lag patterns both globally and locally. In this paper, we introduce TextPioneer, an interactive visual analytics tool for investigating lead-lag across corpora from the global level to the local level. In particular, we extend an existing lead-lag analysis approach to derive two-level results. To convey multiple perspectives of the results, we have designed two visualizations, a novel hybrid tree visualization that couples a radial space-filling tree with a node-link diagram and a twisted-ladder-like visualization. We have applied our method to several corpora and the evaluation shows promise, especially in support of text comparison at different levels of detail.
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关键词
corpora,text visualization,topical lead-lag,text comparison,tree data structures,adaptive focus + context,node-link diagram,text corpus,twisted-ladder-like visualization,topic context,tree visualization,radial space-filling tree,interactive visual analytics tool,data visualisation,hybrid tree visualization,lead-lag analysis,text analysis,textpioneer,data visualization,computational modeling,data mining,lead,visualization
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